BACE and BMA variable selection and forecasting for UK money demand and inflation with Gretl

Artikel

In this paper, we apply Bayesian averaging of classical estimates (BACE) and Bayesian model averaging (BMA) as an automatic modeling procedures for two well-known macroeconometric models: UK demand for narrow money and long-term inflation. Empirical results verify the correctness of BACE and BMA selection and exhibit similar or better forecasting performance compared with a non-pooling approach. As a benchmark, we use Autometrics-an algorithm for automatic model selection. Our study is implemented in the easy-to-use gretl packages, which support parallel processing, automates numerical calculations, and allows for efficient computations.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 8 ; Year: 2020 ; Issue: 2 ; Pages: 1-29 ; Basel: MDPI

Classification and Topics

• Classification: Wirtschaft
• Subject: Bayesian pooling ; model averaging ; model uncertainty ; MPI

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Błażejowski, Marcin ; Kwiatkowski, Jacek ; Kufel, Paweł
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2020

Further information

• DOI: doi:10.3390/econometrics8020021
• Handle: http://hdl.handle.net/10419/247569
• Last update: 10.03.2025, 11:43 AM CET